^ I - -7
NAVAL POSTGRADUATE SCHOOL
Monterey , California
THESIS
A FRAMEWORK FOR MATCHING USER
NEEDS TO AN OPTIMAL LEVEL OF
OFFICE AUTOMATION
by
Arnold John Van Ruitenbeek
A ^ ^
June 1988
Thesis Advisor: T.R. Sivasankaran
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(Include Security Classification) A FRAMEWORK FOR MATCHING USER NEEDS TO AN OPTIMAL
LEVEL OF OFFICE AUTOMATION
12. PERSONAL AUTHOR(S)
VAN RUITENBEEK,
Arnold John
13a. TYPE OF REPORT
Master's Thesis
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FROM TO
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1988 June
15
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16 SUPPLEMENTARY NOTATION The views expressed in this thesis are those of the author
and do not reflect the official policy or position of the Department of
17.
COSATI CODES
18 SUBJECT TERMS (Continue on reverse if necessary and identify by block number)
FIELD
GROUP
SUB-GROUP
Office automation, strategy, organizational per-
formance, equipment selection, office environment
19. ABSTRACT (Continue on reverse if necessary and identify by block number)
This thesis introduces the concept of determining an organization's
optimal office automation strategy by investigating seven characteristics
commonly used by office managers to describe their organizations.
These organization characteristics are size, structure, geographic
dispersion, task, technology, environment, and employee skill. These seven
characteristics form the input into an office automation framework which
' mathematically determines which of three office automation strategies is
best for a particular organization. These three strategy levels are called
low level operational control, mid level management control, and high level
strategic control. The newly determined office automation strategy can in
turn be used to choose appropriate systems analysis methods for the organ-
ization, and for the follow-on purchase and integration of an office
automation system.
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1 T.R. Sivasankaran
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408-646-2637
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A Framework For Matcning User Needs
to an Optimal Level of Office Automation
by
B.
Arnold Jonn ^Van Ruitenbeek
Lieutenant/ United States Coast Guard
S./ University of California/ Davis/ 1977
Submitted in partial
requirements for
fulfillment of tne
tde degree of
MASTER OF SCIENCE IN TELECOMMUNICATIONS SifSTEMS MANAGEMENT
from tne
NAVAL POSTGRADUATE SCHOOL
JUNE 198d
ABSTRACT
This thesis introduces the concept of determining an
organization's optimal office automation strategy by
investigating seven characteristics commonly used by office
managers to describe their organizations.
These organization characteristics are size, structure,
geographic dispersion, task, technology, environment and
employee skill. These seven character i st ic s form the input
into an office automation framework which mathematically
determines which of three office automation strategies is
best for a particular organization. These three strategy
levels are called low-level operational control, mid-level
management control, and high-level strategic control. The
newly determined office automation strategy can in turn be
used to choose appropriate systems analysis methods for the
organization and for the follow-on purchase and integration
of an office automation system.
i i i
Thec./s
V503
C.f
TABLE OF CONTENTS
I. INTRODUCTION 1
A. A FRAMEWORK: THE STARTING POINT 1
B. THE COST OF USING PAPER IN
OFFICE ENVIRONMENTS 2
C. PERSPECTIVES IN OFFICE AUTOMATION DECISION
MAKING 3
II. A SYSTEMS PERSPECTIVE OF OFFICE ENVIRONMENTS 6
A. DIVERSITY IN OFFICE ENVIRONMENTS 8
B. A SYSTEMS VIEWPOINT - 10
1. Financial Measures 11
2. Quality Measures 11
3. Competitive Measures 12
4. Organizational Health Measures 12
C. QUANTIFICATION OF ORGANIZATIONAL PERFORMANCE
METRICS 13
D. NON-SYSTEMS ANALYSIS ISSUES 14
E. OA STRATEGY STILL FOUND LACKING 14
III. A SURVEY OF SYSTEM ANALYSIS METHODOLOGIES 15
A. BIAIT - 15
B. CRITICAL SUCCESS FACTOR ANALYSIS 20
1. Financial CSFs 21
2. Competitive Strategy CSFs 21
3. Environmental CSFs 22
4. Temporal CSFs - 22
C. BUSINESS SYSTEMS PLANNING 24
D. GENERIC DATALOGICAL ANALYSIS 27
i V
t
“ - T ,
E. SELECTING AN OA STRATEGY 28
IV. A FRAMEWORK FOR OFFICE AUTOMATION STRATEGIES 30
A. ORGANIZATIONAL CHARACTERISTICS 31
1. Size 31
2. Structure 33
3. Task 34
4 . Techno 1 ogy 36
5. Employee Skills 37
6. Environment 38
7. Geographical Dispersion 40
B. THE THREE LEVELS OF OFFICE AUTOMATION 40
C. CHOOSING A LEVEL OF OFFICE AUTOMATION 42
0. AN ILLUSTRATION OF THE OA FRAMEWORK 49
E. RESULTS GAINED THROUGH THE USE OF THE OA
FRAMEWORK - 51
APPENDIX A. OA IMPLEMENTATION GUIDELINES - 54
APPENDIX B. NON-SYSTEMS ANALYSIS CONCERNS 63
LIST OF REFERENCES 69
INITIAL DISTRIBUTION LIST 71
V
LIST OF TABLES
I. BIAIT QUESTION TABLE 18
II. LEVELS OF OFFICE AUTOMATION 41
III. ORGANIZATIONAL CHARACTERISTICS 44
IV. OFFICE AUTOMATION LEVEL DETERMINATION 48
V. EXAMPLE OF INPUTS INTO THE OA EQUATION 50
VI. OFFICE AUTOMATION COSTS 68
I. INTRODUCTION
Office automation (OA) is the application of data
processing and telecommunications technologies to the task
of managing business information. The word "office" in
office automation is often associated with a room filled
with desks, telephones, and file cabinets. An office,
however, can also take on many other forms; for example
people whose occupation involve extensive traveling may use
a motel room or the front seat of their car for an office.
For the purposes of this thesis an office is "any place
where managerial, professional, and clerical workers are
engaged primarily in handling business information."
( Barcomb , 1981 , pp . 1 )
The word "automation" is defined as the process of
"substituting some device or machine for a human activity"
(Parsons, 1985, pp. 99). The word automation originated in
the automobile manufacturing industry in the 1930's as an
easier to pronounce substitute for the term automatization.
A. A FRAMEWORK: THE STARTING POINT
Office managers now face a pro 1 i f erat i on of computers
that increases both the scope and the complexity of the
technological choices through which the manager can perform
office tasks more efficiently. In the absence of a general
1
framework, managers will find it difficult to determine the
degree of office automation that would ideally suit their
organization.
This thesis is designed to help office managers choose
an office automation strategy which is best suited to their
needs by providing them with a reference framework which
optimizes their office automation choices using a process
outlined in this thesis. This process takes into account
the characteristics of the organization investigating office
automation technologies and determines which level of office
automation is most suitable for the organization.
B. THE COST OF USING PAPER IN OFFICE ENVIRONMENTS
Often the large "hard dollar" cost of starting up and
operating an office automation system is of great concern to
office managers and their budget approving supervisors.
Although this concern has its rightful place, an office
manager should note the existing costs associated with their
current procedures for the production and storage of paper
records .
In 1977 the annual cost to maintain document files was
nearly 15 cents per page, including labor, depreciation on
file cabinets, and cost of floor space; by 1980 that
figure is estimated to have risen to almost 20 cents per
page. ...The cost to complete, and store for five years, a
full file cabinet of forms is estimated to cost over
$42,000 in 1980 dollars. (Barcomb, 1984, pp. 9-10)
Office automation systems can electronically replace
many of these paper-based transactions, and thereby replace
2
the paper documents created during the manual transaction
process. The replacement of expensive paper based systems
can offset a portion of an automated system's cost.
However, the main point here is not that office automation
systems can be operated at less cost that manual transaction
systems but that operating exclusively with naper records is
not as inexpensive as it may first appear.
C. PERSPECTIVES IN OFFICE AUTOMATION DECISION MAKING
Office managers, who supervise offices in which the
primary means of communication is conducted via the routing
of paper, are becoming concerned about their decreased
competitive stature attributable to their inability to
retrieve needed information in a timely and accurate
fashion.
Many managers feel they are losing control over the
very information that is central to the viability of their
organizations. Other managers, who are directed to meet
increased productivity mandates, are faced with increased
work loads without commensurate increases in personnel
resources. Still other managers are attempting to complete
activities within apparently unrealistic deadlines. Office
automation is specifically directed at these management
concerns and others.
Managers look to office automation for improved office
productivity in their work place. Six common office
3
automation effectiveness measures are often cited by
managers as reasons for automating activities which were
previously done manually. These six reasons are (SENN,
1984 , pp . 38 ) :
1. Faster transaction processing
2. Better accuracy and improved consistency
3. Faster information retrieval
4. Integration of business activities
5 . Reduced cost
6. Better security
However, the use of these six office automation
effectiveness measures, individually or collectively, is
short sighted and narrow in scope. A more realistic
approach is presented in the following text:
The real objective of office automation is to improve the
performance of an organization's business operations....
The artifacts of office operation are not ends in
themselves, but exist only to enable the office to
accomplish its business mission. ...Most offices, as
opposed to factories, do not have products of intrinsic
economic value. While producing twice as many automobiles
for the same amount of resource is an undeniable
improvement in productivity, producing twice as many
documents (or having twice as many communications) is not
an inherently valuable change....
Increasing the efficiency with which office tasks are
performed is only of interest if it yields an improvement
in the realization of the business function that is the
real mission of the office. The goal of office automation
should be increased effectiveness of business operations,
rather than increased efficiency in information handling.
(Hammer, 1982, pp. 247-8)
Although the perspective above is a more useful one, it
widens rather than closes the gap between a random
4
collection of OA equipment picked out of a vendor's catalog
and an effective operational OA system. This thesis will
help office managers bridge this gap by helping them
determine which level of office automation best meets the
needs of their particular organization.
The OA selection process is closely related to the
implementation process, and the success of these two
processes are very interdependent. For the benefit of the
general reader, an introduction to the implementation of OA
systems is provided in Appendix A.
5
II. A SYSTEMS PERSPECTIVE OF OFFICE ENVIRONMENTS
Office automation offers managers solutions to many of
their office productivity problems. However, few of these
productivity improvements will be realized by managers if
they attempt to directly automate their inefficient manual
information processing methods. To the contrary, these
managers will operate just as poorly or worse. In addition
to failing to achieve higher productivity levels, these
managers will also have the added burden of paying for
expensive office automation equipment, thereby still further
reducing their overall cost/benefit productivity measure.
Conversely, being efficient within the limits of an all
paper office does not guarantee a smooth transition to
automation. Too often office managers treat office
automation products, such as free standing computers or
local area networks, as black boxes which are somehow
intrinsically endowed with an understanding of their
particular office and its specific functions. One of the
largest misunderstandings non-users and new users have
regarding office automation is assuming that an office
manager's understanding of an office function is the
equivalent of an office automation system correctly
processing that function.
6
Consequently, one of the most difficult tasks a manager
faced with the prospect of automating his office has is
"telling" his office automation equipment, and the vendor
who supplied the equipment, how his particular office staff
goes about attaining their goals, and how his office inter-
relates with customers and other offices within his
organization.
A careful review of the activities and information flow
patterns of an office should be undertaken prior to
automating these previously manual functions. This formal
process of describing how information enters an
organization, how it is used and how it affects the outputs
of an organization is called systems analysis.
A systems analysis of an organization is a crucial step
in the process of automating previously manual functions; it
is also a crucial step in redesigning existing automated
systems .
For large organizations a systems analysis is often
conducted by a team of office automation consultants. A
manager of a large organization rarely completes the systems
analysis himself because it is unlikely that he has a
thorough enough understanding of how his organization
functions, how his information uses are integrated together,
and how his staff interacts with activities external to his
office. Insufficient time to devote to this task is another
reason these managers do not complete the analysis
7
themselves, although where feasible, it is to a manager's
advantage to follow as closely as possible the systems
analysis of his office. This familiarity with the analysis
will increase his ability to critically evaluate the OA
consultant's recommendations regarding modifications to his
office procedures.
However, in smaller organizations the opposite may be
true, consultants in this case are not the only means of
developing a systems analysis. To the contrary, office
managers may best be able to prepare themselves for the
transition from manual to automated office processing by
accurately and completely identifying their information flow
patterns without outside system analysis assistance.
But as with the larger organizations noted earlier, the
manager must first determine how much of his office should
be automated. That determination must be made first or else
time and money will likely be wasted analyzing office
activities that do not justify being automated. The office
manager needs a decision tool to help him determine what OA
strategy best suits his organization. This decision tool is
the reference framework discussed in the follow-on chapters
of this thesis.
A. DIVERSITY IN OFFICE ENVIRONMENTS
Not all organizations are created equal in their
characteristics, and therefore, no panacea in the form of a
8
single all-purpose analysis can suffice for describing how
information is used in all organizations. As an example,
seven dual-answer questions are listed below to indicate the
wide variety in business information environments:
Does the business in question:
1. Bill customers or accept cash only transactions?
2. Deliver goods at time of sale or later?
3. Record customer profiles or are no records kept?
4. Sell products at fixed or negotiated prices?
5. Sell or lease its products?
6. Record to whom products were sold or are no records
kept?
7. Make products to order or are they selected from stock
on hand?
These seven dual-answer questions can differentiate
between many different types of internal business
environments. These questions are not presented here to
fully define an office's information flows, but are used
here to illustrate the rich diversity found in the full
spectrum of business activities. (Carlson, 1979, pp. 6)
Imagine how differently an independent single-site
retail ice cream business would answer these seven questions
and how different its information needs are in comparison to
a 15 partner law firm. As a result, a systems analysis of
these two businesses would reveal widely differing
information flows and interactions, and hence their office
automation needs would also be drastically different.
9
B. A SYSTEMS VIEWPOINT
A systems analysis is most beneficial when it
encompasses a broad view of office activities. The analysis
should be conducted from a business perspective that takes
in the operation, mission, and goals of the entire
organization in which the automated office will be situated
( Hammer ,
1982 , pp .
249). Only
by understanding how
a n
office
is currently operatirig
can a systems analysis
identify
potential
improvements
that can be brought
to
fruition
through the
introduction
of automated methods.
There is no substitute for coming to grips with the
substance of the office's work. ...The focus of the plan
should be the development of a strategy by which office
systems can contribute to the improved operation of the
company's business activities. The key, therefore, to
success in planning and implementing office automation is
a thorough understanding of the characteristics,
activities, and needs of the organization. Planning for
office automation should focus on the company, on its
business strategies and processes, and on the problems and
opportunities inherent in these. (Hammer, 1982, pp. 251-2)
Improvements gained through automation are centered
around increasing various types of business performance
measures, therefore the first step in the systems analysis
is to identify these performance measures. No organization
has a single performance measure nor are all measures of
equal importance. Individual organizations, in response to
their specific business environment must choose which
performance measures are appropriate for them and weight
these measures accordingly. Many of these performance
10
measures can be grouped into four general categories, namely
financial measures, quality measures, competitive measures,
and organizational health measures.
1 . Financial Meas ur es
Financial measures a>^e those performance character-
istics which can be directly expressed in monetary terms.
Common measures in this category include cost reductions in
regard to existing and regularly reoccurring office
activities and cost avoidance associated with the expense of
new office activities and the increased cost of expanding
existing office activities.
Specific examples of financial measures include
organizational cash flow and return on investment.
2 . Q uality Measures
Quality measures relate to how well an organization
conducts its operations. The speed at which an office
activity takes place and hence the time it takes to complete
the activity is a universal quality measure. Although the
accuracy and consistency of office transactional processing,
in some organizations, can be a more important quality
measure then speed, as is the case with accounting and
engineering applications.
Flexibility is another quality measure.
Organizations operating in fast changing environments or who
deal in custom products may place a heavier emphasis on
11
flexibility than organizations operating in a highly
structured environment.
3 . Competitive M easures
The third category is a grouping called competitive
measures, these measures "relate to the performance of an
organization in the context of the marketplace." (Hammer,
1982, pp. 250) The size of an organization, its market
share, public image, and growth rate are intrinsic
competitive measures.
Common external competitive measures are the
stability of the external business environment, customer
base fluctuations, innovation of competing organizations,
and the price sensitivity of products or services provided
by the organization.
4 . Org a niz ati on al Health Meas ures
Organizational health measures "indicate how well
the unit is functioning as an organization, which in turn
can have a major impact in its business perf ormance . " One
of the most important of these is employee morale.
Secondary measures in this category include absenteeism,
turnover rates, and quality of life issues such as job
content and advancement opportunities.
One of the first uses of office automation systems
was word processing. This change in some instances was met
with great user resistance due to the marked decrease in
organizational health measures that accompanied the arrival
12
of word processing. Many companies in an effort to
efficiently use the new word processing equipment moved the
secretaries into typing pools to keep the equipment in use
to the fullest extent possible. This organizational change
destroyed the working relationship that previously existed
between managers and secretaries.
Two sharply negative results occurred as a result
of losing this vital relationship. Managers who had
secretaries personally reporting to them suffered a loss of
status and loss of non-typing clerical support that their
secretaries provided. Secondly, the secretaries found
themselves in new jobs which had greatly reduced job
satisfaction metrics and extremely limited advancement
opportunities. Consequently, failure to take into account
all the pertinent performance measures yielded a sub-optimal
office automation solution in this situation. (Meyer, 1983,
pp . 68 )
C. QUANTIFICATION OF ORGANIZATIONAL PERFORMANCE METRICS
As noted in the previous paragraphs, not all benefits
are measured in hard cost-saving dollars, this however, does
not negate these value-added benefits.
Although value-added benefits are generally more relevant
to top management than cost savings, they are more
difficult to measure objectively - in the same way that a
manager's worth and performance are difficult to appraise.
(Meyer, 1983, p. 66)
In an effort to complete a quality systems analysis, it
should be kept in mind that it is more beneficial to
13
"roughly measure significant benefits than to accurately
measure trivia" (Meyer, 1983, pp. 66). On the other hand,
if a certain benefit of an office automation system is not
measurable or quantifiable then there is doubt the benefit
ever existed. (Hammer, 1982, pp. 250)
D. NON-SYSTEMS ANALYSIS ISSUES
Office managers considering a new or expanded OA system
should also concern themselves with additional consider-
ations which are outside the context of this thesis. A
brief discussion of these considerations can be found
Appendix B.
E. OA STRATEGY STILL FOUND LACKING
Categorizing performance measures and quantizing these
measures are necessary steps in determining an optimal OA
system for an organization. However some type of OA
strategy must be identified before hand to make this OA
selection process efficient, thus better ensuring a
beneficial and workable Oa solution for the organization. A
reference framework is presented in chapter four of this
thesis which will assist office managers and others in
determining the correct OA strategy for an organization.
14
III. A SURVEY OF SYSTEM ANALYSIS METHODOLOGIES
The previous chapter introduced the concept of viewing
an organization from a system analysis perspective which
relates the interaction of various organizational activities
and determines their attendant performance measures.
There are many different types of systems analysis
methods available to managers who plan on automating all or
portions of their offices. This chapter will describe four
methods that are in common usage and reviews the ability of
each to identify an organization's optimal OA strategy.
A. BIAIT
Business Information Analysis and Integration Technique
(BIAIT) is a system analysis method developed from research
conducted by Donald C. Burnstine. The research began with a
collection of 300 information handling questions. After
reviewing the questions and their implications it was
determined that seven of these questions could "uniquely and
systematically characterize the way an organization uses
informat ion-- independent of its size and independent of the
product or services it provides." (Carlson, 1979, pp. 5)
Of the seven questions, answers to the first four
describe the way the organization relates to its customers,
and the answers to the remaining three questions describe
the characteristics of the entity being ordered.
15
To place these seven questions into perspective five
definitions or ground rules evolved. The first concerns
the notion of an "order". An order, in a BIAIT context, is
anything that triggers a response from a supplier. It can
be something as straight forward as a purchase order, or it
can be as informal as a question received over the
telephone .
The second ground rule states that the entity being
ordered must be either "a thing, a space, or a skill."
(Carlson, 1979, pp. 5) A thing, like a bolt, is applicable
to a product oriented business, whereas a space, like a seat
on an airplane going from New York to San Francisco, or a
skill, like brain surgery, is more applicable to service
oriented businesses.
The third ground rule concerns the perspective of the
person conducting the analysis. Since the analysis is
conducted for the business, all transactions should be
viewed from the the perspective of the supplier rather than
the customer.
The concept of a customer and supplier is broadly
defined here to include transactions completely confined to
the internal workings of the organization, such as
engineering assigning a work order to production to
manufacture a item for use by the organization's engineering
staff .
16
The fourth rule allows businesses to process multiple
types of orders each with differing characteristics, the
seven BIAIT questions can therefore be answered differently
for each type of order.
The last rule restricts answ<^'~s to the seven questions
to one of two answers for each question. The dual answer
format yields a total of 14 answers which theoretically
describes 128 (two to the seventh power) different business
environments.
Furthermore, the BIAIT analysis can be conducted at
multiple management levels within the organization. The
analysis can occur at up to three different levels within
the organization, these three levels are the
E nterpr i se/E stab 1 i shmen t level, the department level, and
the occupation level. The seven BIAIT questions, each
phrased at the three management levels, are illustrated in
Table I.
Little imagination is needed to see parallels in
information handling between different management levels
within the organization. As an example consider the fourth
BIAIT question concerning pricing. The difference is quite
small between concept of fixed and negotiated prices for
products sold by the organization in relation to the lower
level BIAIT parallel of costed work orders and work orders
based on standard rates. Both levels view the
product/serv i ce as either a standard item or a custom
ordered item.
17
TABLE I.
BIAIT QUESTION TABLE
(Carlson, 1979, pp. 6)
Supplier Questions
Organization Level
Billing?
Del i ver
Later?
P r of i 1 e
Customers
Negotiate
Price?
Enterprise/
Establishment
bill or
take
cash
later
or
now
r ecor d
previous
orders from
source or
no profile
negotiate
or fixed
Department
cost
center
or
budget
plan
work
or
fire
call
record
previous
orders from
source or
no profile
costed
work
order or
standard
rate
1
Occupation !
1
i
commis-
sion or
salary
1
piece
work or
hourly
wage
self-
sched-
uled or
' p r i 0 r -
ity
set by
others
record
previous
orders from
source or
no profile
costed
work
order or
standard j
irate i
\
1 :
!
Ordered Entity
Questions
Rented?
Tracked ?
Made to Order?
Organization level
Enterprise/
Establishment
i
rented
or sold
record who
received or
no record
made/assemb led
to order or
from stock
1
Department
loaned
or given
record who
received or
no record
assemb 1 e/create |
or provide ,
f r 0 m f i 1 e s j
Occupation
loaned
or given
record who
received or
no record
assemb 1 e/create !
or provide I
f r 0 m f i 1 e s j
18
Using BIAIT analysis method at multiple levels within
the organization allows the person doing the analysis, a
consultant or the office manager himself, to build a generic
information handling model of the office before any mention
of OA equipment is made. The seven BIAIT questions become
the outline for interviews held with various members of che
office staff. The choice of who is interviewed depends on
what level witnin the organization one is trying to ■^odel.
At
the occupation
level.
interviewing the
emp 1 oyee
filling
the job
being
modeled
i s
an excellent
starting
point.
In some
cases ,
higher
level
supervisory
personnel
may be
r e q u i r e d
to add
answers
to the
seven basic
questions
when the employee is not familiar with all the types of
orders he is required to process. Similar interviews with
other appropriate members of the office staff, the office
manager, and the office manager's supervisor are conducted
to answer the seven BIAIT questions in the context of the
two higher levels in the organization. This multi-level
analysis also determines who in the organization creates a
piece of data and it also identifies who the users of the
information are once it's created.
Using a generic information handling model, built on
the BIAIT analysis, a manager can form a statement of need
on which OA vendors can demonstrate their equipment's
capability to fill that office manager's need for product
intensive information processing.
19
By its very nature BIAIT system analysis tends to be a
product oriented analysis, and conversely does not not give
much weight to office activities not directly supporting the
production of goods and services. Consequently a BIAIT
analysis may not adequately address non-production oriented
activities within the organization.
An OA strategy as determined by a BIAIT analysis will
be almost exclusively transact ionally oriented regardless of
which OA strategy is optimal for the organization. A BIAIT
analysis should only be considered as a follow up analysis
when a transactional OA strategy is correctly identified as
optimal via the reference framework discussed in chapter
four of this thes i s .
B. CRITICAL SUCCESS FACTOR ANALYSIS
Another type of system analysis is called Critical
Success Factor (CSF) analysis. CSF is based on interviews
with managers regarding their goals and the success factors
they feel are critical to the attainment of those goals.
Therein defining the "significant information needs"
required to measure possible organizational improvements
regarding
CSFs.
Normally three
to six
factors are
determined
to be
critical to the
success of
a manager .
Since more
than
one manager is
general 1 y
i nter V i ewed ,
multiple sets of CSFs are likely to occur. In many cases
the analyst has to realize that different managers have
20
different task assignments and different objectives. It is
up to the person conducting the CSF analysis to combine
conflicting manager CSFs into an overall organizational set
of CSFs. Due to the sources of information used in CSF
analysis, OA designs based on this type of analysis are
heavily top-down structu*"ed. The needs of top management, as
expressed in their CSF, are assigned more weight when
determining the organization's overall CSF. (Rockart, 1979,
pp. 84-5)
^ • F inancial CSFs
Critical Success factors originate from four basic
categories. The first category revolves around the
structure of the industry the organization is competing in.
For-profit organizations have making a profit as one of
their major critical success factors. Cash flow and
price/earnings ratios are measures of the profit CSF and as
such they become "significant information needs" of the
organization. (Rockart, 1979, pp. 86)
2. Compe titive St rate gy CSFs
The second category is competitive strategy.
Competitive strategy concerns
factors
such
as
1 ow
cost
producer s
within the industry.
distribution
of
resources
among an
organization's product line.
the
rate
of
new
product development within the industry, and the
organization's market niche defensibility. Industry
position relates to how many competitors are in a particular
21
market and the market share distribution among those
competitors. (Rockart, 1979, pp. 86)
^ • Envir onmen tal CSFs
The third CSF category is environmental factors.
Many CSFs deal with conditions external to the organization.
Availability of raw materials and government regulations are
common examples of factors in this category. An
environmental factor can be the primary CSF for managers in
some industries. However, being external to the manager
does not mean that the manager has no control over these
factors or that he cannot monitor the variables which
measure improvements in this CSF area. (Rockart, 1979, pp.
86 )
4 . Temporal CSFs
The fourth and last CSF category is temporal
factors. These factors are short-term in duration and
commonly surface in management by exception reporting
systems. These factors have become CSFs because they are
below an acceptability threshold and therefore critically
impact the present operation of the organization. (Rockart,
1979, pp. 87)
OA systems designed to meet CSF management control
needs "must be tailored to the specific industry in which
the company operates and to the specific strategies that it
has adopted;" furthermore, it must also record variables
which monitor organizational improvements in relation to
CSFs. (Rockart, 1979, pp. 86)
22
CSF analysis is beneficial because it helps
managers focus on variables which affect their CSFs,
therefore with this analysis method they derive the greatest
organizational benefits from their analysis efforts. The
emphasis of the CSF analysis is on identifying and measuring
variables which affect the organization's CSFs, thereby
defining the scope of information required by the
organization. This definition of scope eliminates the cost
of collecting excess information and reduces the information
overload managers are often exposed to during a systems
analysis. {Rockart, 1979, pp. 88)
Identification of CSFs also prevents organizations
from building an OA system around the information that is
easiest to collect rather than the significant information
relevant to CSF areas. {Rockart, 1979, pp.88)
CSFs are often changing and consideration should be
given to the flexibility of the OA system to meet
organizational factors which were heretofore not considered
critical, or to meet completely new CSFs occurring as a
result of changes internal and external to the organization.
On the other hand, a properly completed CSF
analysis
may
identify
CSFs which are
manager
specific or
temporal
i n
nature
and these CSFs
should
be weighed
accordingly in the overall OA system for the organization.
{Rockart, 1979, pp. 88)
23
A CSF
analysis
i n
itself
does
not identify
the
extent of OA
r e q u i r e d
to
assist
top
managers in
the
monitoring of their CSFs. An OA system purchased solely to
monitor top management CSFs may fail due to the non-
availability of the basic organizational data upon which top
management CSFs are based. A framework must first be used
to identify the organization's OA strategy, from that point
an organization can better determine how OA can assist in
monitoring the organizational variables which effect its
CSFs.
C. BUSINESS SYSTEMS PLANNING
Business systems planning (BSP) was developed in 1975
by International Business Machines (IBM) to help
organizations design an information systems plan that takes
on the perspective of top management and is integrated into
the overall business plan of the organization. The first
two phases of BSP, identification and definition, comprise
the systems analysis portion of the BSP study, and hence it
is of interest to someone about to start a systems analysis
of an organization.
BSP, unlike CSF analysis, takes a business-wide top
management approach that is very broad in scope. BSP covers
many functional areas of a business and attempts to
integrate them into one view of the organization. From this
one view of the organization, BSP defines the systems and
24
subsystems necessary to meet the information needs of the
organization and outlines the requirements for implementing
these systems during later phases of the BSP. (Couger, 1982,
pp. 237)
The first objective of the BSP identification phase is
to "develop an overall understanding of the business" and
determine how its data processing activities support the
business. Inputs to this phase include the current
organizational structure, profiles of the existing manual
and automated informations systems, reports generated by the
organization, and the results of previous systems analyses
performed, if any. (Couger, 1982, pp. 247)
The second objective of this phase is to "identify a
gross network of information systems that will support the
business" and within this network determine which subsystems
are most needed and/or have the highest payback
possibilities. Lastly, the identification phase "develops
an action plan" for the follow-on definition phase. (Couger,
1982, pp. 247)
"The objective of the definition phase is to develop a
long-range information systems plan" that will ensure that
"the business's information resources will be effectively
used". This plan is based on the specific information needs
of the business and is detailed enough to provide managers
with guidance regarding who in the organization is
responsible for what implementation activities along with
how and when to do these activities. (Couger, 1982, pp. 279)
25
Specifically, the information systems plan should be a
vehicle to facilitate communication between functional
areas, and should provide top management with the
information they need regarding their control of the present
BSP phase and the follow-on phases. (Couger, 1982, pp. 280)
The value of BSP lies in the fact that it is top-down
structured and bottom-up implemented. In the structure
portion of BSP "top management involvement establishes
organizational objectives and direction, as well as agreed-
upon system priorities" and sets forth consistent data
standards for the entire organization. Furthermore, the
bottom-up implementation is "management and user oriented
rather than data processing oriented." (Couger, 1982, pp.
239 )
Using BSP analysis, a business develops "an assessment
of future information systems needs based on business
related impacts and priorities" but remains "relatively
independent of the organization's structure" (Couger, 1982,
pp. 239). From a systems perspective, BSP is "an evaluation
of the effectiveness of current information systems"
(Couger, 1982, pp. 239) that goes on to outline an
information systems plan which sets implementation
priorities based on organizational needs and early returns
on OA investments. Thus it can be a powerful tool in the
hands of a manager trying to determine his office automation
requirements in the long run.
26
The scope of BSP is very large and therefore the
systems analysis in support of BSP will also be very large
and costly. If managers had a reference framework that
could quickly identify and therefore contain the scope of
the systems analysis the BSP and other analysis could be
more effectively conducted.
D. GENERIC DATALOGICAL ANALYSIS
Datalogical analysis views business information in a
very microscopic way, rather than from the broad perspective
taken in the analysis techniques discussed above.
OA systems, which appear to meet the needs of an
office, normally have software incorporated into them that
has the ability to store and handle the individual pieces of
data used in that office. However, some caution in this
area is appropriate.
During vendor demonstration of OA systems, office
managers are strongly encouraged to ensure that their data
characteristics are compatible with the OA system. As an
example, if an office is presently using a manual record
keeping system which is based on a nine character customer
identification code {i.e.. Social Security Number) then the
OA system under consideration should have the ability to
store at least a nine character customer code. If this is
not the case, managers must consider the cost of converting
the office data into a form compatible with the new OA
27
system.
This
additional
cost should
not be
confused with
the unavoidable
cost
of
input ing the
data into the
system
during
original
start
up .
S i m i 1 a r 1 y ,
if the
office
has a
customer mailing list with overseas addresses then the OA
system should be flexible enough to store those types of
addresses, or a situation will exist where a sub-optimal OA
system forces users to meet equipment requirements rather
than the other way around.
Unfortunately this type of systems analysis does little
to guide an organization toward its optimal OA strategy and
suffers from the lack of a clearly definable end point. In
this case a manager is never sure when enough analysis has
been conducted or if the analysis previously conducted is of
any benefit to the organization's optimal OA strategy.
E. SELECTING AN OA STRATEGY
Chapters two and three of this thesis discuss the
concept of viewing an organization from a systems
perspective, citing commonly used system analysis
methodologies. However it can be noted that an effective
systems analysis needs a goal in order to provide the
information an office manager needs. A high quality system
analysis may provide an office manager with a large amount
of very accurate information regarding his organization's
information flows, but this information may be of
questionable valve when that office manager sits down to
decides to what extent he will automate his office.
28
Completing a systems analysis could be done more
efficiently if the manager doing the analysis knew before
hand what OA strategy best suited his organization. The
next chapter of this thesis is designed to guide an office
manager through the decision process that determines the
optimal OA strategy for his or any other organization.
After an OA strategy has been selected then a follow-on
system analysis could be more effectively focused on target
information flows which could benefit from the newly
identified OA strategy.
29
IV. A FRAMEWORK FOR OFFICE AUTOMATION STRATEGIES
Although management scientists have researched
organizations in detail, there seldom have been studies
undertaken to determine a general reference framework that
is useful in selecting an optimal office automation strategy
for an organization. Since management scientists have
tended to emphasize the characteristics of the organization
under consideration, a starting point in developing such a
framework is to use those characteristics as a basis for
office automation strategy distinction. Since organizations
have many different characteristics to distinguish them from
other organizations, it is quite evident that no one office
automation strategy will suit all organizations.
Therefore a person tasked with determining which office
automation strategy to pursue, must somehow decide which
organizational characteristics he should consider. Then he
must collect and organize these characteristics into some
type of format from which he can determine the optimal
office automation strategy for the organization.
This thesis presents a framework by which decision
makers can determine the optimal OA strategy for a
particular organization. A framework is defined as "a
systematic set of relationships" or "a conceptual scheme,
structure, or system" (Gove, 1961, p. 902).
30
The framework presented here is a system in which
inputs, in the form of selected organizational
characteristics, are used to make a decision regarding the
selection of the optimal office automation strategy for a
particular organization.
A. ORGANIZATIONAL CHARACTERISTICS
As noted earlier, the optimal choice of office
automation strategies is based on organizational
characteristics. From the many characteristics which
describe an organization's informational needs, seven
characteristics were
chosen as
inputs
for
the
office
automation strategy
f ramework .
A
list
of
these
organizational characteristics are noted below:
- Size
- Structure
- Task
- Technology
- Employee Skills
- Environment
- Geographical Dispersion
These input characteristics are examined individually in the
following sections of this thesis.
1 . Size
From an informational point of view, the best
metric for measuring the size of an organization is the
number of employees on its payroll. (Miles, 1980, pp. 61-
62) .
31
Large organizations are not just small
organizations on a larger scale. As organizations grow,
certain areas in the organization grow at faster rates than
others. The Birmingham Study conducted by the Aston Group
in England observed that as organizations increase in size,
a larger percentage of the organization is directed toward
support activities, and conversely, a smaller percentage is
directed toward primary production activities. As the
primary production workflow became a smaller percentage of
the organization's total activities, the impact of
technological change in that proportionally smaller area
also has a proportionally smaller impact on the total
organization. (Miles, 1980, pp. 55-56)
In summary, the Birmingham Study discovered an
inverse relationship between the size of a given
organization and the extent to which specific production
related technological changes can impinge upon the total
organization. (Miles, 1980, p. 63)
The size of an organization also plays an important
role in determining the speed at which information can be
collected manually and the amount of effort required to
collect that information. In cases where the nature of
other organizational characteristics by themselves do not
justify a higher level of office automation, the size
constraint of larger organizations in regard to the timely
collection of information and efficient use of finite
32
management resources may justify higher levels of office
automation.
In regard to office automation strategies, a low
level of office automation is optimal for organizations with
less than 50 employees, and a high level of office
automation is optimal for large sized organizations with
more than 1000 employees.
2 . Str uct ure
A major factor in the success of organizations is
their structure. It gives individuals in the organization
the ability to specialize using an organization's structure
to assign tasks in support of a single objective, thereby
completing in groups, those objectives which are too complex
to be performed on an individual basis. Specialization also
allows complex organizational objectives to be completed
more efficiently than could be done on an individual basis.
(Miles, 1980, p. 51)
Structure is the design by which organizations are
subdivided; it also outlines the lines of authority and
lines of communication between divisions. The division and
specialization aspects of an organization's structure
determines how work is assigned, and how resources are
allocated to those work assignments. (Chandler, 1981. p.
23)
The characteristic of structure has two basic
metrics by which to measure it. The first metric is the
33
tallness measure of a structure, this relates to how many
management levels exist in the organization. The second
metric is a measure of how wide the organization is, this
relates to how many separate units are identified within
each management level.
The unique input into the office automation
framework gained from the structure characteristic is the
number of management layers in the structure of an
organization. The remaining structure metric, the number of
separate units in an organization, contains redundant
information when compared to the size and task
characteristic inputs into the framework, and therefore is
not addressed here as part of the structure characteristic.
(Miles, 1980, pp. 19-20)
In regard to office automation strategies, a low
level of office automation is optimal for organizational
structures with one level of management control, and a high
level of office automation is optimal for organizations with
five or more levels of management control. Organizations
which have a organization structure that lies between the
two extremes above would be best served by a mid level
office automation strategy.
3 . Task
The number of tasks performed by an organization is
closely related to the number of individuals employed to
complete those tasks. Therefore, to describe the task
34
characteristic in this manner would make it redundant to the
size characteristic described earlier.
A better description of the task characteristic, in
relation to the informational needs of an organization, is
found in depicting the degree of routineness involved in
tasks.
Some tasks are accomplished using an extremely
limited variety of inputs and are completed in a constant
well defined manner. Under these circumstances there is
little variety associated with the task and or its possible
outcomes. Tasks completed under these circumstances are
classified as routine tasks.
Other tasks are classified as nonroutine. In these
instances there are no well established inputs or methods
for completing the task, nor are there strictly defined
outcomes or standards of success associated with the task.
(Perrow, 1970, p. 75)
The organizational characteristic of task has two
metrics by which to measure its routineness. The first
metric is "task variability", a measure regarding "the
number of exceptions encountered" in a task. The second
metric of nonrout i neness is "task coping difficulty", a
measure of "the amount of search [effort] needed to find
successful methods to adequately respond to task
exceptions". (Perrow, 1970, pp. 70)
35
In regard to office automation strategies, a low
level of office automation is optimal for organizations
which operate using routine tasks, and a high level of
office automation is optimal for organizations which operate
using mostly nonroutine tasks. Organizations whose tasks
are best described as semi-routine would be optimally served
by a mid level office automation strategy.
4 . Techno log y
Another major factor in the success of organ-
izations is the technology it uses. Technology improves the
organization's ability to complete a task more efficiently,
when compared to the technology base line of accomplishing
the same task using strictly hand tools/hand labor.
The development and persistence of complex organizations
is in part determined by the extent to which their members
can (1) identify and understand the mix of technologies
and tasks required to meet operative goals and (2) design
and implement appropriate structures of control and
coordination to meet these task requirements. (Miles,
1980, p. 51)
Technology is defined as "the science of the
application of knowledge to practical purposes" (Gove, 1961,
p. 2348). In the context of organizations, technology may
be viewed as the application of knowledge to organizational
tasks to facilitate the completion of these tasks with
reduced expenditure of organizational resources.
The metric used to measure technology is the degree
to which specialized knowledge is incorporated into the
organization.
36
In regard to office automation strategies, a low
level of office automation is optimal for organizations
using primarily unassisted hand tool/hand labor methods to
accomplish tasks. A high level of office automation is
optimal for organizations using state of the art methods or
for those who are developing a method which in the future
will become the state of the art method in their industries.
Lastly, organizations which use established technologies and
practices require a mid level of office automation.
5 . Employee S kill
Skill variety is one of five core job dimensions
used to describe job enrichment. It also has an impact on
the amount of information an employee must have in order to
complete his or her assigned tasks. The remaining four
dimensions are either inputted into the office automation
framework by another organizational characteristic or do not
affect the informational needs of the organization and hence
are not used as inputs into the framework. (Hackman, 1981,
p.335)
Employees must attain certain skill levels in order
to meet the skill variety portion of their job description.
These employee skill levels can be measured by the length of
time required to train employees to complete a certain task
and by the aptitude requirements necessary to become
proficient at that task. The notion of training is used
broadly here to include on-the-job training and the
37
employee's formal full-time education completed prior to his
or her entry into the organization.
The concept of employees should be looked at from
the perspective of the whole organizational payroll, and not
narrowly restricted to just those individuals with primarily
information handling job descriptions. The type of skills
under consideration in determining skill variety levels
include both technical and management skills required to
complete assigned tasks.
In regard to office automation strategies, a low
level of office automation is optimal for organizations
which require a low variety of employee skills i.e. minimal
reading and writing skills. A high level of office
automation is optimal for organizations which require a high
variety of specialized employee skills. Lastly,
organizations which require a moderate amount of employee
skills require a mid level of office automation.
^ • En vir o nment
Organizations thrive only when the environment and
the organization mutually sustain each other. The
organizational characteristic of environment encompasses all
the factors which affect the organization but remain
external to the organization.
For example, organizations take in revenue from the
environment and release their outputs for sale into the
environment. In more specific examples, the federal
38
government establishes regulations regarding the safety of
the workplace which affect the organization, and in the
other direction, the organization, through advertising,
attempts to influence its environment.
The metric used to measure the environmental input
into the office automation framework is the environment's
rate of change. Organizations which operate under strict
government control or who are predicted to remain operating
in the same manner 10 years in the future are described as
being in a stable environment. Organizations which operate
in new industries where no set business practices or
established customer base exist are considered to be
operating in a fast changing environment. (Lawrence, 1981,
p.167)
The rate at which an organization is subject to new
environmental considerations is largely responsible for the
rate of change of character i st i cs internal to the
organization. Therefore, the environmental rate of change
is also a good measure for the rate of change of the whole
organization.
In regard to office automation strategies, a low
level of office automation is optimal for organizations
which operate in a stable environment. A high level of
office automation is optimal for organizations which operate
in a continually fast changing environment. Lastly,
organizations which operate in slow to moderate changing
environments require a mid level of office automation.
39
7 . G e 0 g r a p h i c a 1 Ois p e r s i o n
The characteristic of geographical dispersion is
independent of size or structure. It is the measure of how
many different locations an organization has under its
control and how far apart the two most mutually distant
locations are.
The least geographically dispersed organization has
only one location, therefore the distance measure does not
apply in this case.
In regard to office automation strategies, a low
level of office automation is optimal for organizations
which occupy only a single site. A high level of office
automation is optimal for organizations which occupy sites
dispersed nationally or internationally, and a mid level of
office automation is optimal for regionally dispersed
organizations with less then seven locations.
B. THE THREE LEVELS OF OFFICE AUTOMATION
In order to include as large a segment of potential
office automation users as possible, the concept of office
automation will be viewed from three levels. These three
levels are called low level, mid level, and high level
office automation. The types of organizational control and
the highest automated functions available at each level are
illustrated in Table II. Within each level of Table II OA
functions are internally ranked, however the intralevel
40
ranking and interdependence is not as absolute as with the
interlevel rankings.
The OA levels in Table II are interrelated in such a
manner that functions associated with lower levels in table
II must be in place to support higher level functions when
higher level office automation functions are desired. This
concept of implied lower level functionality is consistent
throughout all three functional levels of office automation
as noted in the equations below:
Operational Control Functions = f(WP,TP)
Management Control Functions = f ( WP , TP , SF , DBMS , DOS )
Strategic Control Functions = f(WP,TP,SF,0BMS,00S,ES,DS)
TABLE II.
LEVELS OF OFFICE AUTOMATION
LOW LEVEL--OPERATIONAL CONTROL FUNCTIONS
1. Word Processing (WP)
2. Transaction Processing (TP)
MID LEVEL--MANAGEMENT CONTROL FUNCTIONS
3. Spreadsheet Forecasting (SF)
4. Data Base Management System (DBMS)
5. Decision Support Systems (ODS)
HIGH LEVEL--STRATEGIC CONTROL FUNCTIONS
6. Expert Systems (ES)
7. Distributed Systems (DS)
41
An example of this inter-relationship between office
automation levels is data base management systems; they
require input data about the organization in order to
produce management control information. This data capture
function is completed by the transaction processing function
at the low level of the office automation system.
In a similar manner, expert systems, at the strategic
control level, requires the use of lower functions such as
the decision support system for its operation, and in turn,
the decision support system needs both the data base
management system and the transaction processing functions
to operate.
The opposite of this interrelationship is not true.
Applications at lower levels of office automation do not
need higher levels of office automation to process office
information. Transaction processing and word processing
can, and frequently do, operate independently of higher
level office automation functions. Similarly, data base
management systems functions at the management control level
can operate without the benefit of expert system functions
at the strategic control level of office automation.
C. CHOOSING A LEVEL OF OFFICE AUTOMATION
Due to the interrelationship between the levels of
office automation noted in the previous section, office
automation decision makers are left with choosing from one
42
of three office automation strategies. These three
strategies correspond to the three levels of office
automation noted in Table II.
The difficulty inherent in this choice stems from the
fact that seven independent characteristics have been
identified as affecting the informational needs of an
organization. Therefore, seven characteristics affect the
decision process regarding the correct matching of an
organization's informational needs to the optimal level of
office automation. At this point it appears a great deal of
information must be taken in as inputs to the office
automation selection framework before an optimal office
automation strategy can be selected.
Table III lists these seven organizational
characteristics along with the range of descriptive values
each characteristic can take on. Ranges for
characteristics listed in Table III are broken down into
three regions with a short description of each region.
These three descriptions are listed in the three columns
marked "A", "B" and "C" of Table III.
Column "A" denotes a region of the character i st ic range
which indicates a low level of office automation is required
for that characteristic. Whereas column "C" denotes a
region at the opposite end of the range for an individual
characteristic, this region indicates that a high level of
office automation is required for this particular
43
TABLE III
ORGANIZATIONAL CHARACTERISTICS
COLUMN
COLUMN
COLUMN
CHARACTERISTIC
"A"
"B"
"C"
LESS
50 TO 100
MORE
SIZE
THAN 50
EMPLOYEES
THAN 100
EMPLOYEES
EMPLOYEES
STRUCTURE
ONE
2,3, OR 4
5 OR MORE
LAYER
LAYERS
LAYERS
GEOGRAPHICAL
SINGLE
REGIONAL
GLOBAL
DISPERSION
SITE
TASK
ROUTINE
SEMI-
NON-
ROUTINE
ROUTINE
TECHNOLOGY
HAND
ESTABLISHED
STATE OF
LABOR
TECHNOLOGY
THE ART
ENVIRONMENT
STABLE
SLOW
FAST
CHANGING
CHANGING
EMPLOYEE SKILLS
LOW
MEDIUM
HIGH
VARIETY
VARIETY
VARIETY
44
characteristic. Column "B" denotes the mid region in the
range of a characteristic, a middle ground between the two
extreme regions listed in columns "A" and "C" of Table III.
Characteristics with values in the column "B" region
indicate a mid level of office automation is required.
Splitting the range that organizational characteristics
can take on into three regions and then limiting the value
of the seven organizational characteristics to only one of
these three regions, scales down the problem of determining
the appropriate level of office automation. Instead of
accepting as inputs into the office analysis framework an
infinite number of organizational characteristic
combinations, only 2187 (three to the seven power)
combinations exist when framework input data is limited to
the seven characteristics broken down into three value
regions.
Ideally, a mapping of all 2187 combinations to specific
levels of office automation would be indicated. However to
keep the framework tractable, another matching strategy will
be presented here. Actual mapping of the individual 2187
combinations to a particular office automation strategy is
left as follow-on work to this thesis.
The values for the seven informational characteristics
must be combined into one measure which the office
automation decision maker can use to determine the level of
automation appropriate for a particular organization. This
45
combining activity is accomplished mathematically using the
following formula:
OA coefficient = ( A * . 14 ) + ( B * . 79 ) + ( C * 1.43 )
Where the symbol indicates the multiplication of
the two numbers within the parentheses. The variable A in
the above equals the number of characteristics in the
organization which can be described by the values in column
"A" of Table III. Similar definitions for the variables B
and C in the above formula can be related to the appropriate
columns in Table III. In all cases, the sum of variables
"A", "B" and "C" must equal seven.
It was decided that for convenience of usage the range
of valid office automation coefficients would extend from
one to ten. Designing the OA coefficient equation to this
output range meant that an organization in which all seven
character i sties could be described by column "A" values
would be given an OA coefficient of one. Dividing one by
seven yields approximately .14; therefore, each Column "A"
characteristic would add .14 to the total OA coefficient.
Likewise, an organization in which all seven
characteristics could be described by column "C" values
would be given an OA coefficient of ten. Dividing ten by
seven yields approximately 1.43; therefore, each Column "C"
character i st ic would add 1.43 to the total OA coefficient.
46
The midway point on the OA coefficient scale is 5.5,
therefore an organization in which all seven characteristics
could be described by column "B" values would be given an OA
coefficient of 5.5. Dividing 5.5 by seven yields
approximately .79, therefore, each Column "B" characteristic
would add .79 to the total OA coefficient.
The three explanations above do not cover the remaining
2184 combinations of organizational characteristics possible
with seven characteristics constrained to three values each,
but the OA coefficient formula is applicable to all 2187
combinations of organizational characteristics possible.
Any combination of A, B and C, which describe the values of
the seven characteristics for a specific organization, can
be calculated to determine that organization's OA
coefficient.
The relationship between any OA coefficient determined
from the formula above and the correct level of office
automation is given in Table IV.
The break point in Table IV between the operational
level and the management level represents the half way point
between 1 and 5.5, the "perfect" operational OA score and
the "perfect" management OA score respectively. Likewise,
the break point in Table IV between the management level and
the strategic level represents the half way point between
5.5 and 10, the "perfect" operational OA score and the
"perfect" management OA score respectively.
47
TABLE IV.
OFFICE AUTOMATION LEVEL DETERMINATION
OA Coefficient Range Office Automation L eve 1
Less Than 3.25
3.25 To 7.75
Greater Than 7.75
LOW LEVEL - Operational Control
MID LEVEL - Management Control
HIGH LEVEL - Strategic Control
OA coefficients which border on transition points in
Table IV should be reviewed to determine if any of the seven
informational characteristics extend out of the bounds of
the tri -level choices. That is, does a characteristic
measure smaller than the column "A" descriptor or larger
than the column "C" descriptor? In this case the required
office automation level may be decreased to a lower level
when one or more values of organizational characteristics
are smaller then the column "A" descriptor. Similarly the
office automation level may be increased to a higher level
when one or more values of organizational characteristics
are larger then the column "C" descriptor.
In rare cases this out-of-bounds situation may occur to
an extreme. In the opinion of the person doing the OA
determination one characteristic may appear to warrant the
organization a different level of office automation from the
level indicated by the OA coefficient formula. Office
automation decision makers are warned not to disregard or
48
weigh lightly the OA level determined using the OA
coefficient formula above.
As an alternative to the outright dismissal of the OA
coefficient determination, the reader in redirected to table
II. In the table the seven office automation functions are
listed in rank order from the lowest OA level to through to
the highest OA level. Although the OA coefficient is not as
strong a indicator of which specific functions a particular
organization is best suited to within an OA level; it could
in border line cases, indicate that only the lowest numbered
function in the higher of the two OA strategies levels
should be considered. Or a phased approach may be
indicated. Organizations could install an OA system to meet
the requirements of the lower level OA strategy and later
expand to meet the requirements of the higher level OA
strategy.
D. AN ILLUSTRATION OF THE OA FRAMEWORK
Assume an office automation decision maker is faced
with the task of determining the correct level of office
automation for an organization with the following
characteristics:
- Size
- Structure
- Dispersion
- Task
- Technology
- Environment
- Emp 1 oyee Skills
350 Employees
More Than Five Layers
Goba 1
Routine
Established Technology
Fast changing
Low Variety
49
This set of organizational characteristics will yield
two "A" values, two "B" values and three "C" values as shown
in Table V .
TABLE V.
EXAMPLE OF
INPUTS INTO
THE OA
EQUATION
COLUMN
COLUMN
COLUMN
CHARACTERISTIC
"A"
" B"
"C"
Size
Str ucture
X
X
Dispersion
Task
X
X
Techno 1 ogy
Environment
X
X
Employee Skills
TOTAL
X
T"
"3“
The OA coefficient formula for this organ izatioh looks
like the following:
OA Coefficient = (2 * .14) + (2 * .79) + (3 * 1.43)
The OA coefficient for this organization is calculated
to be 6.15, therefore referring to Table IV, the framework
states the optimal office automation strategy is mid level
office automation, the management control level. This
organization should incorporate an OA strategy which
includes, in an integrated fashion, the following OA
functions; word processing, transaction processing,
spreadsheet forecasting, data base management systems, and
decision support systems.
Execution of the framework by this organization
resulted in a clear OA direction and a specific end point.
50
both of which were lacking prior to the use of the Office
Automation Framework. Now the organization can design an
optimal office automation system. Whereas without the use
of the Office Automation Framework, an office automation
attempt could have resulted in either a slowing evolving set
of semi -compatible OA upgrades or in the purchase of a
grossly oversized OA system which would have overtaxed the
resources and hence the profitability of the organization.
E. RESULTS GAINED THROUGH THE USE OF THE OA FRAMEWORK
Office managers using the Office Automation Framework
will avoid the pit falls suffered by office managers who
attempt to design an OA system without first completing this
extremely important step.
The OA Framework provides an organization with a method
of bounding the size of their OA effort by producing a
functional end point which directs the organization in a
clear manner. A follow-on systems analysis of the
organization can now be focused on only those tasks
currently done manually which have OA corollaries identified
by the framework as being appropriate for the organization.
As an additional benefit, an organization using the OA
framework is spared the cost and frustration of
incrementally expanding and retrofitting their OA system to
meet originally unconsidered requirements which were later
identified as critical to the organization's conversion to
automated methods.
51
Conversely, an organization using the framework is also
spared the high cost of purchasing, installing and
maintaining an OA system which is in excess of their needs.
Through the purchase of an optimal OA system the
organization receives the best cost/benefit return from
their conversion from manual to automated office
procedures. As a result the organization's competitive
stature in relationship to other organizations within the
same industry, and other organizations in general, is
greatly improved.
One of the most important benefits of the Office
Automation Framework lies in its ability to provide an
organization with an integrated approach to automating
manual functions. A known OA strategy can be applied from
the original systems analysis through to the final
determination of which OA vendor and OA system configuration
is optimal for the organization. The framework provides an
environment which allows office managers the opportunity to
fully investigate the i n ter r e 1 a t i o n sh i p s between seemingly
separate tasks which have been identified as candidates for
automation. This investigation of the organization's task
interaction yields the maximum synergistic benefit from the
installed OA system.
Another major contribution of the Office Automation
Framework is its ability to draw together an office manager
and OA professionals into a structured environment that
52
quickly yields an optimal OA strategy for the organization.
The execution of the Framework in a quick and straight
forward manner, as demonstrated earlier, produces an OA
strategy that can be consistently followed from the original
systems analysis of the organization, as discussed in
chapters two and three of this thesis, right through to the
equipment selection and user training noted in Appendices A
and B .
Office Managers with extremely limited OA familiarity
can, by examining seven characteristics of an organization,
determine the optimal OA strategy for that organization via
the Office Automation Framework. Inputs to the Framework
are common organizational characteristics expressed in a
management context familiar to office managers. This allows
non OA professions, like office managers, to confidently
choose the correct office automation strategy for their
organization and therefore bound the size of the OA effort
appropriate for their organization.
53
APPENDIX A.
OA IMPLEMENTATION GUIDELINES
A. TRANSITION TO OFFICE AUTOMATION
Regardless of what other actions an office manager
takes in connection with the conversion of his office from
paper to automated systems, the way he chooses to implement
his new system has the most effect on the success of the
whole endeavor. A good implementation strategy can reap
substantial rewards from an office automation system which
is somewhat sub-optimal for a particular office environment.
OA implementation is the process of bringing together
people, equipment, and procedures to form a smooth running
unit. Of these three, the proper integration of the people
element, the office staff, into the picture is most
critical to the success of the OA implementation. (Chafin,
1982, pp. 86)
A great deal has been written in the OA literature
regarding how the office staff should be introduced to the
concept of working with automated systems. The two examples
below are representative of the topic.
The importance of addressing the concerns of the people in
the office cannot be over emphasized. The introduction of
automated systems and related new work methods represents
a major change in the office. Office workers will have
natural concerns about health and safety, privacy, job
security, job content, and a host of other issues.
Uncertainty is a breeding ground for resistance. (Hammer,
1982, pp. 251)
54
When a company undertakes an office automation effort,
the question of job security soon crosses the minds of
most employees. Unless that question is answered, lack of
cooperation, tacit undermining, a talent flight, and other
undesirable results may occur. Senior management's
information strategy should include written assurance from
the chief executive that office automation will not result
in loss of jobs. (Barcomb, 1981, pp. 21)
People are the biggest asset in any office, or in any
organization. A loss of this valuable asset in an attempt
to make it more productive and hence more valuable is an
ironic but all too likely event when OA systems are poorly
imp 1 emented .
1 . Dealing with OA Fears
A successful implementation strategy is based on
two major principles. The first addresses the removal of
barriers to office automation. The greatest of these
barriers is fear, particularly fear of change and fear of
job loss in connection with the office automation effort,
a. Fear of Personnel Reductions
A prime motivating factor for automating
office activities is the reduction of personnel costs, one
of the largest costs an office manager is faced with. This
rational, however, is short sighted. A stated management
policy of no personnel cuts due to automation, along with
support for the argument that the same number of individuals
are more productive using an OA system, can effectively
counter a great deal of implementation resistance on the
part of the office staff. In this manner, through increased
55
productivity, the cost effectiveness of the OA system can
still be maintained without the negative connotation of
staff reductions .
Even members of the staff whose job security
is assured would be affected by the personnel reorganization
which results from personnel cuts. This reorganization
would be disruptive to the established communication paths
which are vital to the smooth and efficient operation of the
organization. The reorganization itself would also add
additional stress to an already stressful changing office
environment.
Managers, who prior to automation did not use
a typewriter are less likely to directly use many of the OA
system's functions, particularly tasks which place a heavy
emphasis on information input into the OA system, therefore
clerical help will still be part of the office staff in a
fully automated office. (Oleatt, 1985, pp. 7) All the above
factors tend to negatively bias personnel reductions as a
cost justification measure for OA systems,
b . Fear of Change
User resistance is also rooted in the fear of
change .
The first hurdle for new office system users is the
feeling of fear and strangeness they have about the new
machine. ...But, you have to overcome this fear or the user
will simply not be in the proper mood for the user
training phases of the OA implementation. (Henderson,
1982, pp. 730)
56
Members of an office staff, like most people,
are likely to resist change either actively or passively.
This fear of change can be overcome by involving the staff
in the selection and implementation of the new office
automation system. "Informing them of the OA goals [for
their office], soliciting their contributions, and
reassuring them that their concerns will be addressed"
should make great strides toward overcoming the fear that is
associated with a change to automated methods. "Appropriate
corporate policies should be established and articulated by
senior management" to ensure that staff input has
credibility in the formulation of the office's automation
strategy. (Hammer, 1982, pp. 251)
2 . OA User Incentive s
The second major principle in a successful
implementation strategy concerns the creation of incentives
for using automated office systems. An office staff will be
reluctant to change their work habits unless it is
demonstrated that this change will be in their best
interest. Therefore, the choice of OA applications
introduced during system implementation should benefit both
the organization and the users who must change their methods
of operation to accommodate the new system. (Meyer, 1983,
pp. 64) "Before you start teaching in earnest, give the
user small but tangible successes. This helps users get
over feelings of fear about the usefulness of the new OA
57
system." (Henderson, 1982, pp. 731) Early user success will
reinforce a positive attitude toward the OA system and will
build momentum for more automated procedures in the follow-
on stages of the OA implementation. (Meyer, 1983, pp. 64)
B. USER REJECTION OF NEW OA SYSTEMS
Conversely, OA implementation will suffer from user
rejection when, from a users' perspective, the OA system is
difficult to operate, and users still have access to
alternate manual methods of completing their tasks. When
rejection occurs, it is likely that the users had little or
no input into the automation process, and the human factors
of implementing the OA system were largely ignored by the
system planners. (Chafin, 1982, pp. 86)
C. BENEFITS OF HIGH QUALITY USER TRAINING
The user training package that comes with an office system
can help make or break the system. ..success of an office
system depends almost entirely on how its users view
it. ...Users of an office system will depend more on their
first impressions about the system than users of systems
designed for other user types, like application
programers. If the office system doesn't seem useful
after users try it for a short period of time (measured in
hours), then they are not going to dig through the
system's intricacies to figure it out. (Henderson, 1982,
pp. 729)
One of the greatest aids in overcoming user resistance
to office automation is through a training program designed
to match the needs of new system users to the particular
system being implemented. "This reinforces the idea that
this machinery was installed to help the office staff do the
58
job better and easier." (Lipoma, 1982 , pp. 723 ) A high
quality long-term training program smooths the transition
between manual and automated procedures in the office
environment. This program, along with reaping the benefits
of reducing user fear, can become the prime vehicle for
modifying the orientation of the office staff toward
accepting automated procedures as common place and ordinary.
The follow-on step to this reor i entat ion then becomes making
the full-time use of the OA system the new standard method
of accomplishing various office tasks.
A quality training program is also the most visible
sign of upper management concern for the office staff. From
the user perspective, the program shows that they, the
office staff, are as important as the "machines" in the new
office concept being developed in their work place.
D. DEALING WITH TECHNOSTRESS
Craig Brod coins the term "technostress" to describe
the emotional stress induced by the introduction of new
technology. (Brod, 1984, pp. 28) Technostress has a very
negative effect on the productivity of people who use OA
systems. Common indicators of technostress are very slow
learning curve improvements, high error rates, and blocked
communication channels within the office structure (Brod,
1984, pp. 47). Brod suggests overcoming technostress using
a strategy which divides adaptation to computers into three
phases called orientation, operations and mastery.
59
1. Orientation
The first phase is called orientation. Orientation
begins three months before the automated system is placed
into operation. During this phase system implementors meet
with the office staff to explain the OA system and its
intended impact on the office. Orientation may include
placing the OA equipment in the office and making it
available for viewing and experimentation. Meetings with
future OA users during this phase should insure that the
users have an accurate concept of what the system can do and
what is expected of the users when the system goes into
operation. It is particularly important for system
implementors to address excessively negative or positive
expectations on the part of potential users and to resolve
issues users have regarding the conversion to automated
methods. (Brod, 1984, pp. 46)
2 . Operation s
The second phase of the adaptation is called
operations; it begins when the office staff actually starts
using the OA system and starts developing a dependence on
the system to complete various office tasks. During this
phase system implementors can reduce stress by "making sure
the office staff understands how the automated system fits
into the office
as a whole."
(Brod, 1984,
pp. 46)
Other
stress reducing
activities
include
developing.
i n
conjunction with
the users ,
OA standards
of control
and
60
standards for OA user performance. These standards can keep
an organization from raising the work standards for people
up to the level of "perfection, accuracy and speed to which
computers have made managers accustomed". A sharp
distinction between what is expected from the OA equipment
and what is expected from the OA users should always be
maintained. (Oleatt, 1984, pp. 9)
Another stress reduccion method applicable to this
phase consists of reducing staff workloads during the
transition to automated procedures, this gives users the
learning time necessary to gain the new skills required to
effectively operate the OA system. "Establishing channels
of communication to handle user f r u s t r a t i o ns , " and promoting
a "buddy system" in which advanced users can help less
advanced users, are also two very important methods to
reduce the stress associated with the operation of OA
systems. (Brod, 1984, pp. 46-7)
3 . Master y
The last phase Brod describes in the adaptation
process is called Mastery. Mastery "exists when skills to
use the machine have been mastered and knowledge is present
to expand computer application." During this phase the
office staff is encouraged to "upgrade their OA skills" and
"suggest new applications to improve productivity".
Establishing user feedback loops regarding standards for OA
system outputs and rewarding users for skills they have
61
learned are also suitable methods for stress relief in the
mastery phase. (Brod, 1984, pp. 47)
Adding too much emphasis to cost controls and
immediate productivity improvements during the
implementation and early operation phases can stifle the
enthusiasm and interest new users have regarding their OA
system, and in the process managers can end up actively
discouraging these users. Office managers should insure
that the people and equipment work well together before they
focus on reaping the productivity benefits of 3 structured
and streamlined OA system. After promulgating structured OA
procedures managers can still maintain user interest and
improve productivity by asking users for suggestions
regarding how these OA procedures can be changed to reduce
costs and increase the performance of the business.
(Strauss, 1983, pp. 26)
E. EQUIPMENT SELECTION BEFORE IMPLEMENTATION
Although the method used to implement an OA system into
an office environment is very important, no realistic
transition to an OA system can occur before an overall OA
strategy is selected. Selection of an appropriate OA
strategy for a particular organization is thrust of this
thesis and is discussed at length in the main body of the
thesis.
62
APPENDIX B. NON-SYSTEMS ANALYSIS CONCERNS
This appendix covers considerations which do not fall
strictly within the bounds of the systems analyses as
discussed in this thesis but are none the less important to
office managers reviewing potential OA systems.
These considerations are divided into two groups called
system tests and physical factors. The following seven
systems tests should be conducted on OA systems which have
been identified for possible use by the organization by the
reference framework and a suitable follow-on system
analysis.
A. SYSTEMS TESTS
^ ‘ Pr ocedure Test
Determine if exactly following the procedures in
the OA system manual yields the proper results. Does the OA
system do all things promised and do all the features of the
OA system work to the user's satisfaction? (Senn, 1984,
pp.539)
2 . Performance Time Test
Measure the response time of OA systems operating
at expected activity levels and in overload conditions
(Senn, 1984, pp.539). If a manager plans on his staff being
able to answer customer inquiries during the same telephone
63
conversation they are received, then the OA system under
consideration must meet that performance time criteria.
3 . Storage Test
The OA system must have enough storage capacity
to keep all working data on file. (Senn, 1984, pp.539) At
some point older data will be archived to tapes or floppy
disks for long term storage. As a guideline for determining
storage needs, "some 35 percent of all filed papers are
never retrieved; 90 to 95 percent are never accessed after
the first year." (Barcomb, 1981, pp. 104)
4 . Peak Load Tes t
An effective OA system must be able to process
the volume of activities that occur when all terminals are
operating at peak processing capacity and the originally
configured OA system should still have reserve capacity for
future expansion needs. (Senn, 1984, pp.539)
5 . Reco very Test
Determine if users can restart the OA system
after a failure has occurred, and determine the maximum
extent to which data can be irretrievably lost. Also
determine how long it takes an OA system to return to full
functionality after a failure occurs. (Senn, 1984, pp.539)
6 . Human F act ors Tes t
Can users use the OA system throughout a complete
work day without undo fatigue? (Senn, 1984, pp.539)
64
7. System Expansion Test
Both stand-alone
single-
user
systems
and
c 1 ustered
systems should be
e va 1 uated
to
determine
their
expansion
capacities in terms
of more
work
stations.
more
data storage and more applications. (Senn, 1984, pp.539)
B. PHYSICAL FACTORS
Prior to installing a particular OA system which
satisfies the systems tests noted above certain physical
factors should be considered to ensure proper operation of
the OA system.
^ * E lectr i ca l Power
Many OA systems require dedicated circuit
breakers and power line conditioning equipment to maintain
the desired level of reliability. In geographical areas
where electrical power does not meet OA vendor requirements
un i nterruptab le power supplies must be installed between the
building electrical service point and the OA system.
^ • Grounding Re qui re ments
OA equipment must be properly grounded for safety
reasons and to ensure proper operation. Directions for
grounding terminals to each other and to the electrical
ground of the building should be followed without deviation.
3 . C ooling Load
OA systems like most large pieces of electronic
equipment give off considerable amounts of waste heat. This
65
coupled with a low tolerance for high temperatures common
with computer equipment creates a potential problem for OA
installations which do not plan for the additional cooling
requirements needed to counter the increased waste heat
produced.
4 . Fire P rotection
Halon systems are the preferred method of
providing fire protection for rooms dedicated to housing OA
systems, the second most preferred method is carbon dioxide
systems. The use of overhead sprinklers will cause the OA
system to be non-operational for an extensive period of time
which would be extremely unfortunate if the "fire" is later
determined to be a false alarm.
5 . Spac e
OA systems occupy space. The work station
portion of OA systems are normally located on the users desk
or at a dedicated table nearby. To derive maximum benefit
from the OA system these new work stations must be
integrated into the user's personal work environment
complimenting non-OA activities.
Furthermore, mass storage devices or central
processing units may require a large portion of a room or a
completely dedicated room for fire protection and security
reasons.
66
6 .
Cable Routing
An OA system with multiple work stations will
require the routing of cables between the various pieces of
equipment that comprise the system. Route planning should
consider abrasion damage to cables, fire codes, and possible
future expansion before determining the final cable routing
configuration.
7 . Security
Information stored in OA systems is one of the
most valuable assets an organization possesses. Its loss or
compromise to competitors can be a major financial loss.
Security measures to prevent unauthorized access to the
information should be in place to protect the information
prior to declaring an OA system operational. Addressing the
topic of data security should not wait until after an
instance of data compromise or loss but should be addressed
when the OA system is originally designed.
OA system installation planning should also
consider physical security of the equipment itself. OA
systems are themselves high value items. Stand alone micro
computers in particular suffer from high theft rates when
situated in uncontrolled office settings. (Senn, 1984,
pp.539)
67
r
o •
IMPLEMENTATION AND OPERATIONAL COSTS
When radically different methods of completing certain
tasks are undertaken, cost estimates regarding those new
methods are difficult to ascertain. A break down of cost
areas incurred when implementing and operating OA systems
are listed in table VI to help office managers estimate the
reoccurring and non-reoccurring costs associated with OA
systems .
TABLE VI.
OFFICE AUTOMATION COSTS
( Kroenke , 1983 , pp . 36 )
IMPLEMENTATION COSTS
System Analysis And System Design
Facilities Preparation
Hardware Costs
Software Costs
System Acceptance Testing
Documentation
One-Time Training
Data Conversion
Data Capture
OPERATING COSTS
User Per sonne 1
DP Personnel
Communications Expense
Electrical Power
Paper Costs
Recurring Training
Backup
Recovery
Hardware Maintenance
Software Maintenance
Documentation Updates
68
LIST OF REFERENCES
Barcomb, David, Office Automation, Digital Press, 1981.
Brod, Craig, "How to Deal With 'Technostress'", Office
Admin istration a nd Autom a tio n, August 1984.
Carlson, Walter M., "Business Information Analysis and
Integration Technique (BIAIT)--The New Horizon", Data Base,
Springl979.
Chafin, Roy L., "Local Computer Networks from a Human
Factors Perspective", 7th Conference of Local Computer
Networks Digest , IEEE Press ,
Chandler, Jr., Alfred D., "Strategy and Structure",
Organization by Design: Theory and Practice, Business
Publications, fiTc 7,' TJSTr
Couger, J. D., Colter, M. A., and Knapp, R. W., Advanced
Sys t em D e velop men t/Feasibility Techn iques , Wiley, 1982 .
Davis, G.B., "Strategies For Information Requirements
Determination", IBM Systems Journal , Vol. 21, No. 1, 1982.
Gove, Philip Babbcock, Editor, Webster's Third New
International Dic ti onary , Merian, 1961.
Hachman, J. Richard, and others, "A New Strategy for Job
Enrichment", Organization by Design: Theory and Practice,
Business Pub 1 1 cafTons^ Tn’cT'^ r9'8T7
Hammer, Michael, "Improving Business Performance: The Real
Objective of Office Automation", 1982 Office Automation
C onference Digest , AFIPS, 1982.
Henderson, Allan J., "Training Packages for Office Systems:
Some Practical Considerations", 1982 Office Automation
Conference Digest , AFIPS, 1982.
Lawrence, Paul R., and Lorsch, Jay W., "Environmental
Demands and Organizational States", Organizatio n by Design :
Theo r y a nd Practice , Business Publications, Inc., 1981.
Lipoma, P., "Education in Train ing--Whose Responsibility",
1982 Office Automation Conference Digest , AFIPS, 1982.
Meyer, N Dean, "Implementing Technology: The Quest for
Support", Data Commun ications , Mid-September 1983.
69
Miles, Robert H., Macro Organizational Behavior, Foresman,
1980.
Oleatt, William A., "Editorial", Office Administration and
Automation, June 1984.
Oleatt, William A., "Editorial", Office Administration and
Automation , June 1985.
Parsons, H. Mclvaine, "Automation and the Individual:
Comprehensive and Comparative Views", Human Factors, V.27,
February 1985.
Perrow, Charles, Organizational Analysis: A Sociological
V i ew , Wadworth, 1 9 /U .
Rockart, John F., "Chief Executives Define Their Own Data
Needs" , Har V ard Business Review, March-April 1979.
Senn, James A., Analysis and Design of Information Systems,
McGraw-Hill, 198 ~ ~
Strauss, Paul, "Managing Information Systems for Payback and
Planning", Data Communications, M i d- Sep tember 1983.
70
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